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Record W2161547889 · doi:10.1598/rrq.36.1.1

Access to Print in Low‐Income and Middle‐Income Communities: An Ecological Study of Four Neighborhoods

2001· article· en· W2161547889 on OpenAlexfundno aff
Susan B. Neuman, Donna Celano

Bibliographic record

VenueReading Research Quarterly · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersUniversity of OxfordUniversity of CambridgeMcGill UniversityHarvard UniversityAmerican Educational Research Association
KeywordsLiteracyReading (process)Low incomeVariety (cybernetics)Early literacySociologyGeographyEconomic growthSocioeconomicsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

ABSTRACTS Building on a growing body of ecological research, this study examines access to print in two low‐income and two middle‐income neighborhood communities in a large industrial city. It documents the availability of print in these communities, focusing on resources considered to be influential in a child's beginning development as a writer and reader. It describes the likelihood that children will find books and other resources, see signs, labels, and logos, public places (spaces) conducive to reading, books in local preschools, school libraries, and public library branches. Results of the year‐long analysis indicated striking differences between neighborhoods of differing income in access to print at all levels of analyses, with middle‐income children having a large variety of resources to choose from, while low‐income children having to rely on public institutions which provide unequal resources across communities. Such differences in access to print resources may have important implications for children's early literacy development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.177
GPT teacher head0.435
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations508
Published2001
Admission routes1
Has abstractyes

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